On the lifecycle of aerosol particles : Sources and dispersion over Scandinavia

Aerosol particles are likely important contributors to our future climate. Further, during recent years, effects on human health arising from emissions of particulate material have gained increasing attention. In order to quantify the effect of aerosols on both climate and human health we need to better quantify the interplay between sources and sinks of aerosol particle number and mass on large spatial scales. So far long-term, regional observations of aerosol properties have been scarce, but argued necessary in order to bring the knowledge of regional and global distribution of aerosols further. In this context, regional studies of aerosol properties and aerosol dynamics are truly important areas of investigation. This thesis is devoted to investigations of aerosol number size distribution observations performed through the course of one year encompassing observational data from five stations covering an area from southern parts of Sweden up to northern parts of Finland. This thesis tries to give a description of aerosol size distribution dynamics from both a quantitative and qualitative point of view. The thesis focuses on properties and changes in aerosol size distribution as a function of location, season, source area, transport pathways and links to various meteorological conditions. The investigations performed in this thesis show that although the basic behaviour of the aerosol number size distribution in terms of seasonal and diurnal characteristics is similar at all stations in the measurement network, the aerosol over the Nordic countries is characterised by a typically sharp gradient in aerosol number and mass. This gradient is argued to derive from geographical locations of the stations in relation to the dominant sources and transport pathways. It is clear that the source area significantly determine the aerosol size distribution properties, but it is obvious that transport condition in terms of frequency of precipitation and cloudiness in some cases even more strongly control the evolution of the number size distribution. Aerosol dynamic processes under clear sky transport are however likewise argued to be highly important. Southerly transport of marine air and northerly transport of air from continental sources is studied in detail under clear sky conditions by performing a pseudo-Lagrangian box model evaluation of the two type cases. Results from both modelling and observations suggest that nucleation events contribute to integral number increase during southerly transport of comparably clean marine air, while number depletion dominates the evolution of the size distribution during northerly transport. This difference is largely explained by different concentration of pre-existing aerosol surface associated with the two type cases. Mass is found to be accumulated in many of the individual transport cases studied. This mass increase was argued to be controlled by emission of organic compounds from the boreal forest. This puts the boreal forest in a central position for estimates of aerosol forcing on a regional scale.

Troposphere Calibration Techniques for Deep Space Probe Tracking

Ground-based Earth troposphere calibration systems play an important role in planetary exploration, especially to carry out radio science experiments aimed at the estimation of planetary gravity fields. In these experiments, the main observable is the spacecraft (S/C) range rate, measured from the Doppler shift of an electromagnetic wave transmitted from ground, received by the spacecraft and coherently retransmitted back to ground. If the solar corona and interplanetary plasma noise is already removed from Doppler data, the Earth troposphere remains one of the main error sources in tracking observables. Current Earth media calibration systems at NASA’s Deep Space Network (DSN) stations are based upon a combination of weather data and multidirectional, dual frequency GPS measurements acquired at each station complex. In order to support Cassini’s cruise radio science experiments, a new generation of media calibration systems were developed, driven by the need to achieve the goal of an end-to-end Allan deviation of the radio link in the order of 3×〖10〗^(-15) at 1000 s integration time. The future ESA’s Bepi Colombo mission to Mercury carries scientific instrumentation for radio science experiments (a Ka-band transponder and a three-axis accelerometer) which, in combination with the S/C telecommunication system (a X/X/Ka transponder) will provide the most advanced tracking system ever flown on an interplanetary probe. Current error budget for MORE (Mercury Orbiter Radioscience Experiment) allows the residual uncalibrated troposphere to contribute with a value of 8×〖10〗^(-15) to the two-way Allan deviation at 1000 s integration time. The current standard ESA/ESTRACK calibration system is based on a combination of surface meteorological measurements and mathematical algorithms, capable to reconstruct the Earth troposphere path delay, leaving an uncalibrated component of about 1-2% of the total delay. In order to satisfy the stringent MORE requirements, the short time-scale variations of the Earth troposphere water vapor content must be calibrated at ESA deep space antennas (DSA) with more precise and stable instruments (microwave radiometers). In parallel to this high performance instruments, ESA ground stations should be upgraded to media calibration systems at least capable to calibrate both troposphere path delay components (dry and wet) at sub-centimetre level, in order to reduce S/C navigation uncertainties. The natural choice is to provide a continuous troposphere calibration by processing GNSS data acquired at each complex by dual frequency receivers already installed for station location purposes. The work presented here outlines the troposphere calibration technique to support both Deep Space probe navigation and radio science experiments. After an introduction to deep space tracking techniques, observables and error sources, in Chapter 2 the troposphere path delay is widely investigated, reporting the estimation techniques and the state of the art of the ESA and NASA troposphere calibrations. Chapter 3 deals with an analysis of the status and the performances of the NASA Advanced Media Calibration (AMC) system referred to the Cassini data analysis. Chapter 4 describes the current release of a developed GNSS software (S/W) to estimate the troposphere calibration to be used for ESA S/C navigation purposes. During the development phase of the S/W a test campaign has been undertaken in order to evaluate the S/W performances. A description of the campaign and the main results are reported in Chapter 5. Chapter 6 presents a preliminary analysis of microwave radiometers to be used to support radio science experiments. The analysis has been carried out considering radiometric measurements of the ESA/ESTEC instruments installed in Cabauw (NL) and compared with the requirements of MORE. Finally, Chapter 7 summarizes the results obtained and defines some key technical aspects to be evaluated and taken into account for the development phase of future instrumentation.

Die Rolle der Globalstrahlung im Klimasystem Südwestdeutschlands

Die Untersuchungen umfassen die Periode 1981 – 2000 und basieren hauptsächlich auf Daten des Deutschen Wetterdienstes (DWD). Relativwerte der Globalstrahlung beziehen sich auf die Rayleigh-Atmosphäre. Das Regressionsmodell nach Angström ermöglicht die Erweiterung des Meßnetzes. In linearer und nichtlinearer Regression und Korrelation ist die Globalstrahlung entweder abhängige (Sonnenscheindauer, Bewölkung) oder unabhängige Variable (Lufttemperatur, Bodentemperatur). Ihre Intensität in Abhängigkeit von Großwetterlagen, Großwettertypen und Luftmassen wird diskutiert. Diesbezüglich werden mit der Linearen Diskriminanzanalyse ähnliche Großwetterlagen und Stationen in signifikant unterschiedenen Gruppen zusammengefaßt, getrennt nach Sommer- und Winterhalbjahr. Abhängig von der Zeit betrachtet, enthalten Globalstrahlung, direkte und diffuse Sonnenstrahlung, Lufttemperatur, Bewölkung und Niederschlag signifikante zyklische Variationen, die gegebenenfalls klimatologisch relevant sind. Weiteren Aufschluß ergeben deshalb die Zeitreihenanalysen. Autokorrelation-Spektralanalysen (ASA) der genannten Variablen werden in integrierten Spektren dargestellt. Hinweise auf die zeitliche Konstanz signifikanter Varianzmaxima enthalten die Spektren der dynamischen (gleitenden) ASA.

Bayesian space-time data fusion for real-time forecasting and map uncertainty

Environmental computer models are deterministic models devoted to predict several environmental phenomena such as air pollution or meteorological events. Numerical model output is given in terms of averages over grid cells, usually at high spatial and temporal resolution. However, these outputs are often biased with unknown calibration and not equipped with any information about the associated uncertainty. Conversely, data collected at monitoring stations is more accurate since they essentially provide the true levels. Due the leading role played by numerical models, it now important to compare model output with observations. Statistical methods developed to combine numerical model output and station data are usually referred to as data fusion. In this work, we first combine ozone monitoring data with ozone predictions from the Eta-CMAQ air quality model in order to forecast real-time current 8-hour average ozone level defined as the average of the previous four hours, current hour, and predictions for the next three hours. We propose a Bayesian downscaler model based on first differences with a flexible coefficient structure and an efficient computational strategy to fit model parameters. Model validation for the eastern United States shows consequential improvement of our fully inferential approach compared with the current real-time forecasting system. Furthermore, we consider the introduction of temperature data from a weather forecast model into the downscaler, showing improved real-time ozone predictions. Finally, we introduce a hierarchical model to obtain spatially varying uncertainty associated with numerical model output. We show how we can learn about such uncertainty through suitable stochastic data fusion modeling using some external validation data. We illustrate our Bayesian model by providing the uncertainty map associated with a temperature output over the northeastern United States.

Impact of irrigation in the Po valley (Italy) on meteorological parameters through numerical simulation

Recent studies found that soil-atmosphere coupling features, through soil moisture, have been crucial to simulate well heat waves amplitude, duration and intensity. Moreover, it was found that soil moisture depletion both in Winter and Spring anticipates strong heat waves during the Summer. Irrigation in geophysical studies can be intended as an anthropogenic forcing to the soil-moisture, besides changes in land proprieties. In this study, the irrigation was add to a LAM hydrostatic model (BOLAM) and coupled with the soil. The response of the model to irrigation perturbation is analyzed during a dry Summer season. To identify a dry Summer, with overall positive temperature anomalies, an extensive climatological characterization of 2015 was done. The method included a statistical validation on the reference period distribution used to calculate the anomalies. Drought conditions were observed during Summer 2015 and previous seasons, both on the analyzed region and the Alps. Moreover July was characterized as an extreme event for the referred distribution. The numerical simulation consisted on the summer season of 2015 and two run: a control run (CTR), with the soil coupling and a perturbed run (IPR). The perturbation consists on a mask of land use created from the Cropland FAO dataset, where an irrigation water flux of 3 mm/day was applied from 6 A.M. to 9 A.M. every day. The results show that differences between CTR and IPR has a strong daily cycle. The main modifications are on the air masses proprieties, not on to the dynamics. However, changes in the circulation at the boundaries of the Po Valley are observed, and a diagnostic spatial correlation of variable differences shows that soil moisture perturbation explains well the variation observed in the 2 meters height temperature and in the latent heat fluxes.On the other hand, does not explain the spatial shift up and downslope observed during different periods of the day. Given the results, irrigation process affects the atmospheric proprieties on a larger scale than the irrigation, therefore it is important in daily forecast, particularly during hot and dry periods.

A Novel Method for the Homogenization of Daily Temperature Series and Its Relevance for Climate Change Analysis

Instrumental daily series of temperature are often affected by inhomogeneities. Several methods are available for their correction at monthly and annual scales, whereas few exist for daily data. Here, an improved version of the higher-order moments (HOM) method, the higher-order moments for autocorrelated data (HOMAD), is proposed. HOMAD addresses the main weaknesses of HOM, namely, data autocorrelation and the subjective choice of regression parameters. Simulated series are used for the comparison of both methodologies. The results highlight and reveal that HOMAD outperforms HOM for small samples. Additionally, three daily temperature time series from stations in the eastern Mediterranean are used to show the impact of homogenization procedures on trend estimation and the assessment of extremes. HOMAD provides an improved correction of daily temperature time series and further supports the use of corrected daily temperature time series prior to climate change assessment.

Feasibility of future epidemiological studies on possible health effects of mobile phone base stations

The increasing deployment of mobile communication base stations led to an increasing demand for epidemiological studies on possible health effects of radio frequency emissions. The methodological challenges of such studies have been critically evaluated by a panel of scientists in the fields of radiofrequency engineering/dosimetry and epidemiology. Strengths and weaknesses of previous studies have been identified. Dosimetric concepts and crucial aspects in exposure assessment were evaluated in terms of epidemiological studies on different types of outcomes. We conclude that in principle base station epidemiological studies are feasible. However, the exposure contributions from all relevant radio frequency sources have to be taken into account. The applied exposure assessment method should be piloted and validated. Short to medium term effects on physiology or health related quality of life are best investigated by cohort studies. For long term effects, groups with a potential for high exposure need to first be identified; for immediate effect, human laboratory studies are the preferred approach.